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A Survey on Deep Learning for Human Mobility
16 references·1 citing·24 second hop
A Survey on Deep Learning for Human Mobility (2021)A Survey on Deep Learning for Human Mobil…Human mobility: Models and applications (2018)Human mobility: Models and ap…Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts (2016)Predicting the Next Location:…Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs (2014)Modeling User Activity Prefer…Dynamic population mapping using mobile phone data (2014)Dynamic population mapping us…Disaster Resilience: A National Imperative (2013)Disaster Resilience: A Nation…A universal model for mobility and migration patterns (2012)A universal model for mobilit…Friendship and mobility (2011)Friendship and mobilityModelling the scaling properties of human mobility (2010)Modelling the scaling propert…Limits of Predictability in Human Mobility (2010)Limits of Predictability in H…Understanding individual human mobility patterns (2008)Understanding individual huma…Climate change-induced migration and violent conflict (2007)Climate change-induced migrat…The scaling laws of human travel (2006)The scaling laws of human tra…Time series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Time Series Analysis, Forecasting, and Control (1995)Time Series Analysis, Forecas…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…The P 1 P 2 D Hypothesis: On the Intercity Movement of Persons (1946)The P 1 P 2 D Hypothesis: On …Predicting urban mobility patterns with a LightGBM-enhanced gravity model: Insights from the Wuhan metropolitan area (2025)Predicting urban mobility pat…The origin of bursts and heavy tails in human dynamics (2005)Reality mining: sensing complex social systems (2005)Growth, innovation, scaling, and the pace of life in cities (2007)Geo-located Twitter as proxy for global mobility patterns (2014)A survey of results on mobile phone datasets analysis (2015)Birds of a Feather: Homophily in Social Networks (2001)Power-Law Distributions in Empirical Data (2009)DeepMove (2018)Power-law distributions in empirical data (2018)Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Forecasting with artificial neural networks: (1998)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Serial Correlation as a Convenient Simplification, Not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England (1978)Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends? (1980)Principles of forecasting : a handbook for researchers and practitioners (2001)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Push-Pull Migration Laws (1983)Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters (2019)Social physics (2022)25 years of time series forecasting (2006)The politics of attention: how government prioritizes problems (2006)
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  • 1995Time Series Analysis, Forecasting, and Control3,494 cited
  • 2010Limits of Predictability in Human Mobility3,230 cited
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  • 2007Climate change-induced migration and violent conflict1,007 cited
  • 2014Dynamic population mapping using mobile phone data908 cited
  • 2014Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs

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  • 2025Predicting urban mobility patterns with a LightGBM-enhanced gravity model: Insights from the Wuhan metropolitan area6 cited